Bacterial Diversity and Functional Analysis of Severe Early Childhood
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www.nature.com/scientificreports OPEN Bacterial diversity and functional analysis of severe early childhood caries and recurrence in India Balakrishnan Kalpana1,3, Puniethaa Prabhu3, Ashaq Hussain Bhat3, Arunsaikiran Senthilkumar3, Raj Pranap Arun1, Sharath Asokan4, Sachin S. Gunthe2 & Rama S. Verma1,5* Dental caries is the most prevalent oral disease afecting nearly 70% of children in India and elsewhere. Micro-ecological niche based acidifcation due to dysbiosis in oral microbiome are crucial for caries onset and progression. Here we report the tooth bacteriome diversity compared in Indian children with caries free (CF), severe early childhood caries (SC) and recurrent caries (RC). High quality V3–V4 amplicon sequencing revealed that SC exhibited high bacterial diversity with unique combination and interrelationship. Gracillibacteria_GN02 and TM7 were unique in CF and SC respectively, while Bacteroidetes, Fusobacteria were signifcantly high in RC. Interestingly, we found Streptococcus oralis subsp. tigurinus clade 071 in all groups with signifcant abundance in SC and RC. Positive correlation between low and high abundant bacteria as well as with TCS, PTS and ABC transporters were seen from co-occurrence network analysis. This could lead to persistence of SC niche resulting in RC. Comparative in vitro assessment of bioflm formation showed that the standard culture of S. oralis and its phylogenetically similar clinical isolates showed profound bioflm formation and augmented the growth and enhanced bioflm formation in S. mutans in both dual and multispecies cultures. Interaction among more than 700 species of microbiota under diferent micro-ecological niches of the human oral cavity1,2 acts as a primary defense against various pathogens. Tis has been observed to play a signifcant role in child’s oral and general health. Dysbiosis among these microbes due to excessive and frequent intake of carbohydrates results in acidic niche, thereby lowering the bufering provided by healthy microbiome. Tis condition leads to demineralization of tooth surface causing caries in children 3,4. Once lesions advance beyond the white spot stage and the enamel surface is damaged, they cannot be biologically reversed resulting in Severe Early Childhood Caries (SC) among the children with the age group of 3–6 years5. Considerable change in persistent oral biota in response to the functional molecules even afer the treatment of SC facilitates recurrent caries (RC) in children, afecting both primary and permanent dentition 6. Moreover, dysbiosis of oral microbes also results in acute to chronic disease conditions either directly or indirectly by producing metabolically active compounds that interrupt host immune system. Various studies have shown that harmful oral microbiome may hold a signifcant impact beyond the oral cavity that is related to systemic diseases7, including elevated cardiovascular risk 8,9, rheumatoid arthritis 10, adverse pregnancy outcome 11 and digestive diseases 12. Such factors make it imperative to know the colonization patterns of oral commensals occurring during childhood and their benign impact in oral and systemic diseases and health conditions. Metagenomics studies with the help of high-throughput sequencing technologies revolutionized the human microbiome research13, providing an opportunity to tap and focus on the unexplored complex microbial systems that are difcult to cultivate in-vitro. Increased understanding about the functional activity of microbes within the complex microbial community with that of host ecosystems was possible with the advancement of computational analysis tools for these sequences14. According to Keystone Pathogen Hypothesis15, understanding and identifying the complex interactions between high and low abundant microbes and its functional potential that resist any therapeutic agents under the micro-ecological niche. Such analysis may prevent an adverse efect on the human system and can become a new target for treatment and preventive care for caries as well as other related diseases. 1Department of Biotechnology, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India. 2Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, Tamil Nadu, India. 3Department of Biotechnology, K. S. Rangasamy College of Technology, Tiruchengode, Tamil Nadu, India. 4Department of Pediatric Dentistry, K. S. R Institute of Dental Science and Research, Tiruchengode, Tamil Nadu, India. 5Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Block 1, Room No. 201, Chennai 600036, India. *email: [email protected] Scientifc Reports | (2020) 10:21248 | https://doi.org/10.1038/s41598-020-78057-z 1 Vol.:(0123456789) www.nature.com/scientificreports/ % of the sum % of top of remaining overrepresented overrepresented Sample ID Study group Gender Age DMFT No. of sequences Unique reads Duplicate reads % Trimmed sequence sequences P1 Normal Female 3 0 324,653 30,867 293,786 0.029 13.8 58.08 P2 Normal Female 6 0 368,052 34,579 333,473 0.03 8.2 64.01 P3 Normal Female 5 0 500,131 51,239 448,892 0.025 11.7 56.07 P8 Normal Female 3 0 843,584 154,048 689,536 0.032 17.4 51.24 P9 Normal Female 4 0 426,340 39,929 386,411 0.029 12.4 57.52 P10 Normal Male 5 0 791,013 69,365 721,648 0.035 1.6 65.50 P11 Normal Male 4 0 1,044,615 87,922 956,693 0.033 2.1 57.34 P15 Normal Male 4 0 989,960 91,168 898,792 0.035 2.7 61.17 P17 Normal Male 5 0 959,351 83,279 876,072 0.034 2.1 63.31 P4 Disease Male 5 5 581,388 62,484 518,904 0.031 8.3 58.69 P5 Disease Female 4 4 541,995 46,244 495,751 0.033 7.1 64.15 P6 Disease Female 5 4 763,526 53,837 709,689 0.033 10.8 65.19 P7 Disease Male 4 4 519,897 44,592 475,305 0.03 17.0 59.49 P13 Disease Female 5 4 928,077 67,115 860,962 0.036 4.4 68.04 P14 Disease Male 6 5 790,177 38,068 752,109 0.038 16.4 64.44 P33 Disease Male 5 5 423,672 37,885 385,787 0.031 13.0 58.97 P35 Disease Male 6 5 976,071 65,141 910,930 0.034 2.1 61.96 P39 Disease Male 6 5 289,569 30,562 259,007 0.031 6.2 65.03 P40 Disease Female 5 4 400,603 43,049 357,554 0.03 6.9 61.39 P19 Recurrent Male 6 2 1,197,632 76,828 1,120,804 0.037 19.5 60.19 P21 Recurrent Female 7 2 963,211 69,289 893,922 0.035 3.8 59.44 P23 Recurrent Male 6 2 946,556 91,744 854,812 0.033 2.4 58.57 P25 Recurrent Female 7 3 916,099 85,611 830,488 0.033 3.8 57.66 P31 Recurrent Female 7 3 980,648 69,794 910,854 0.036 3.7 66.27 P32 Recurrent Female 6 4 1,018,812 56,302 962,510 0.037 9.6 73.01 P36 Recurrent Female 7 3 423,917 39,608 384,309 0.03 8.0 63.27 P37 Recurrent Female 7 2 332,321 44,845 287,476 0.031 9.1 58.15 P38 Recurrent Male 6 3 343,591 38,805 304,786 0.029 7.3 61.88 Table 1. Patient demographic data and QC of NGS data. Here, we report the analysis of both over-represented and under-represented caries causing microbiota, its predictive functional traits, co-aggregation with each other and their susceptibility towards secondary caries in SC and RC of Indian children. Importance was given to the exploration of biomarkers in-order to identify the key pathogen and its functional properties that resist the micro ecological stress. Interaction network analysis among the oral microbiota and functional traits would enhance the understanding about the strong network of oral bacterial species especially in SC and RC that could paves way for early detection and management of dental caries. Results Demography of caries status. In the current report, study subjects were categorized into three study groups and two gender groups. Caries status of the participants, their age and gender are presented in Table 1. Sequencing were performed for 30 samples, Caries Free (CF) (n = 10), Severe Early Childhood Caries (SC) (n = 10), Recurrent Early Childhood Caries (RC) (n = 10), from the 55 children enrolled because of low yield and quality of DNA. Gender proportion (Female/Male) of the study subjects CF, SC and RC were 5/5, 4/6, 6/4 respectively. Signifcant diferences were not observed in the mean age and gender proportion among three study groups. Biodiversity of microbiota among SC, RC and CF micro ecosystem through high quality sequencing. A total of 15,270,361 high quality reads were generated from 28 samples with an average of 391,573 per sample ranging between 110,367 and 772,880 afer trimming out low quality reads (Table 1). High richness in species diversity using Shannon, Chao and ACE index with 52,628 unique OTU’s afer trimming out the low-quality reads were observed. RC exhibits signifcant diference in Chao 1 index with CF (P = 0.039), SC (P = 0.043) and in ACE with CF (0.012) and SC (P = 0.009) (Fig. 1A). Out of 52,628 OTU’s obtained in the analysis SC, CF and RC are characterized by 19,984, 12,473 and 8306 unique OTU’s respectively. SC and CF shared 7314 OTU, CF and RC shared 4556, RC and SC shared 5320 OTU’s. In common 3682 OTU’s were shared by all three study groups. Representative Venn diagram illustrates the number of unique and shared OTUs in each study group (Fig.